Type D personality, quality of life, and physical symptoms in ...

[Pages:18]Type D personality, quality of life, and physical symptoms in the general population: A dimensional analysis

Christie Stevenson and Lynn Williams School of Social Sciences, University of the West of Scotland, Paisley, UK

Abstract

Objective: Type D personality, the interaction of negative affectivity (NA) and social inhibition (SI), has been associated with a range of adverse health-related outcomes in cardiac patients and healthy participants. However, recent studies which have adopted a dimensional approach to Type D found no effect of Type D (NAxSI) on mortality or quality of life, after controlling for its constituent elements. To-date, no study has determined if Type D is associated with negative health outcomes in healthy individuals when conceptualised as a dimensional variable. Design: A cross-sectional self-report study with 177 healthy participants. Main Outcome Measures: Physical symptoms and quality of life. Results: Using the traditional categorical analysis for Type D, it was found that Type D's report significantly more symptoms and significantly lower quality of life than non-Type D's. However, when analysed as a dimensional construct (NAxSI), using multiple regression analysis, Type D (NA x SI) was not a significant predictor of physical symptoms or quality of life, after controlling for the main effects of NA and SI separately. Conclusion: These findings support those of recent studies that have identified null effects of Type D on outcome when analysed as a dimensional construct.

Keywords

Type D, Social Inhibition, Negative Affectivity, Physical Symptoms, Quality of Life,

This is a peer-reviewed accepted author manuscript of the following research output: Stevenson, C., & Williams, L. (2014). Type D personality, quality of life and physical symptoms in the general population: a dimensional analysis. Psychology and Health, 29(3), 365-373. DOI: 10.1080/08870446.2013.856433

Introduction

Type D personality has been defined as the existence of a variety of negative emotions called negative affectivity (NA), paired with the conscious inhibition of the expression of these emotions termed social inhibition (SI). The presence of both NA and SI suggests that Type D's not only experience negative thoughts and feelings but also inhibit the expression of these emotions social situations. Therefore, it was originally proposed that it is the synergy of the NA and SI traits that is key (Denollet, 2005).

Type D personality's association with negative health outcomes has been well documented (e.g., Denollet et al., 1996; Denollet & Brutsaert, 1998; Denollet, Vaes & Brutsaert, 2000), with Type D being related to a threefold increased risk of poor prognosis and morbidity in cardiac patients (Denollet, Schiffer & Spek, 2010). As well as being linked to increased risk of mortality in cardiac patients, Type D personality has also been associated with patient reported outcomes, including lower perceived mental and physical health (Versteeg et al., 2011). A recent meta-analysis by O'Dell, Masters, Spielmans & Maisto (2011) found that Type D was associated with major adverse cardiac events and impaired quality of life.

Although Type D was initially investigated in cardiac patients, several studies have also found that Type D has a negative influence on health in healthy populations. A review by Mols and Denollet (2010) concluded that Type D has a negative impact on mental health status (e.g., symptoms of depression and anxiety) and on physical health status, including more somatic symptoms and lower health status. Similarly, a recent study by Williams and Wingate (2012) found that Type D was associated with increased physical symptoms and stress in the general population. In addition, several studies have identified a link between Type D and potential explanatory pathways in healthy individuals including poor healthrelated behaviours (e.g., smoking and alcohol use) (Bruce, Curren & Williams, 2013;

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Gilmour & Williams, 2011; Svansdottir, van den Broek, Karlsson, Gudnason, & Denollet, 2012; Williams et al., 2008). In addition, there is also evidence of potential physiological mechanisms in the general population, including greater cortisol reactivity to stress (Habra et al., 2003) and higher cardiac output during an experimental stressor (Williams, O'Connor & O'Carroll, 2009).

Despite a large evidence base suggesting that Type D is associated with negative health outcomes, the utilisation of Type D as a dichotomous typology in the majority of these studies has been subject to recent criticism (Coyne et al., 2011; deVoogd, Sanderman & Coyne, 2012; Smith, 2011). Traditionally, the classification of Type D was determined by participant's scoring above the established cut-off point (>10) for both traits (NA and SI) determining whether a participant was classified as Type D or non-Type D (Denollet, 2005). More recently, the use of a categorical approach to Type D has come under scrutiny. Based on their taxometric analysis, Ferguson et al., (2009) suggested that Type D is better represented as a continuous variable, as the multiplicative interaction terms of NA x SI, than as a dichotomous variable. Subsequently, it is then possible to control for the main effects of the constituent elements of Type D (NA and SI) in a regression analysis. Accordingly, the most appropriate test of the predictive utility of Type D is to determine if the multiplicative interaction of NA and SI predicts outcome after controlling for the main effects of the NA and SI. Denollet has proposed that the Type D consists of more than just the presence of negative emotions and that social inhibition is a moderator of the effects of NA on outcome (Denollet et al., 1996). Accordingly the interaction of NAxSI should predict outcome above and beyond the effects of NA and SI independently, if it is the synergistic effect of the constructs that is key. Therefore, analysing Type D as the interaction of NAxSI is arguably the most appropriate analytic method for the construct, and provides the most stringent test of its predictive utility.

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The analysis of Type D in this way has resulted in several recent studies finding no association between Type D personality and mortality among individuals with congestive heart failure and coronary heart disease (Coyne et al., 2011: Grande et al., 2011). In a sample of 700 heart failure patients, Coyne et al., (2011) found that Type D was not associated with mortality. However, the prevalence of Type D in this study was unusually low (13% compared to the usual 27-34%) raising questions over the generalizability of the sample. At the same time, Grande et al., (2011) published data from a much larger study of 1040 participants which again found that Type D did not predict all-cause mortality.

Recently, Williams, O'Connor, Grubb & O'Carroll (2012) investigated the relationship between Type D and psychosocial outcomes in post-MI patients using both the categorical and continuous data analysis strategies found that in a sample of myocardial infarction (MI) patients Type D individuals did report lower quality of life and higher functional impairment than non-Type D individuals when Type D was analysed as a dichotomous typology. However, when analysing through additional regression analyses using the interaction of NA and SI, no significant associations were found between Type D and quality of life. Interestingly, the NA component of Type D was associated with poor quality of life, but the NAxSI interaction term did not predict outcome, nor did the SI component, prompting Williams et al., (2012) to suggest that the NA component of Type D may be the driving force behind the associations found between Type D and subjective outcomes in previous studies.

To-date, all previous research on Type D and subjective outcomes in the general population has analysed Type D status using a categorical typology. Therefore, in line with recent findings, (e.g. Coyne et al., 2011; Williams et al., 2012) the central aim of the current study is to examine for the first time in a non-clinical sample if Type D is associated with subjective outcomes (i.e. physical symptoms and quality of life) when treated as a dimensional variable

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in standard regression analyses, after controlling for the main effects of negative affectivity and social inhibition.

Methods

Participants and Procedure

The sample consisted of 177 staff and students from a Scottish University, recruited on campus via convenience sampling. The sample consisted of 32 males and 145 females with a mean age of 30.0 (age range 17-89). They were given a brief introduction of what the study would require and invited to participate by completing the questionnaire pack. Ethical approval had been obtained from the psychology department's ethics committee prior to testing.

Measures

Type D personality

Type-D personality was measured using the DS14 (Type D Personality Scale: Denollet, 2005), a 14-item scale which measures the two personality traits of Negative Affectivity (e.g. `I take a gloomy view of things') and Social Inhibition (e.g. `I often talk to strangers') in two 7-item subscales. Each statement requires the participant to rate how accurate a reflection of their personality they believe this to be, from 0 (False) to 4 (True). To assess both personality traits individually, the subscales of Social Inhibition and Negative Affectivity can be scored as continuous variables with a range of 0 to 28. Traditionally, participants were classified as having a Type D personality when both SI and NA were 10 (Denollet, 2005). However, using the methods proposed by Ferguson et al. (2009) and treating both SI and NA as continuous variables, we also tested the Type D interaction term (NAxSI). Cronbachs was

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0.86 and 0.82 respectively for NA and SI in the current study, demonstrating a good level of internal consistency.

Physical Symptoms

The Cohen-Hoberman Inventory of Physical Symptoms (CHIPS: Cohen and Hoberman, 1983) is a scale consisting of 33 statements that measure the level of distress or discomfort each of the physical symptoms (e.g., stomach pain) give the participant over a period of 2 weeks, including the day that the questionnaire was completed. Participants indicated this on a Likert scale ranging from 0 (not at all been bothered by the problem) to 4 (the problem has been an extreme bother). Excellent levels of consistency were found for this measure, with a Cronbachs of .92 in the current study.

Quality of Life

The World Health Organisation Quality of Life Questionnaire (WHOQOL-BREF: WHO, 1996) is a 25-item measure that was used to measure the participant's perceived quality of life. On a 5-point Likert scale, participants answered questions indicating how much, how completely and how satisfied they are with each `domain' of their life. The domains were: Physical Health (e.g. `Do you have the energy for everyday life?'), Psychological (e.g. `Are you able to accept your bodily appearance?'), Social Relationships (e.g. How satisfied are you with your sex life?') and Environment (e.g. `Have you enough money to meet your needs?'). Scores are then summed across the domains with scores being scaled in a positive direction (i.e., higher score= higher quality of life). Cronbachs was .86 for the current study, indicating a high level of internal consistency.

Statistical Analyses 6

We analysed the data from this study using two methods, first using the traditional method of classifying individuals as Type D if they scored above the recommended cut-off (10) on both NA and SI (Denollet, 2005). Second, we treated both NA and SI as continuous variables and used the multiplicative term of SI?NA. Initially, an analysis of Type D as a categorical construct was carried out, with independent samples t-tests investigating differences between Type D and non-Type D individuals in physical symptoms and quality of life. In addition, a multiple regression analyses were used to examine if categorical Type D (dummy-coded) predicted physical symptoms and quality of life. Second, Type D was analysed as a dimensional construct, consistent with Ferguson et al. (2009) and correlations were carried out to determine any significant associations between dimensional Type D (NAxSI), NA, SI, physical symptoms and quality of life. Following this, multiple regression analyses were carried out to determine which factors were predictive of quality of life and physical symptoms. Demographic factors (i.e. gender and age) were entered into step 1 of the hierarchical regression, followed by the Type D subscales (NA and SI separately) in step 2. Finally, the dimensional Type D (NAxSI) was entered into the final step. All continuous predictor variables were mean centred before entry into the regression analyses (to control for multicollinearity, as recommended by Aiken and West (1991)).

Results

Prevalence of Type D Personality

From the sample of 177 participants, 62 (7 males and 55 females) were classified as Type D (35%) according to the recommended cut-off points of 10 for the subscales of NA (M= 15.39; S.D= 4.67) and SI (M= 14.4; S.D= 4.48).

Categorical Analysis

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Results from a standard independent samples t-test indicated that Type D individuals have significantly lower quality of life (M=84.68; S.D=10.49) than non-Type D individuals (M=93.65; S.D=9.11), t (175) = 5.91, p ................
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